Results 21 to 30 of about 133,681 (240)

Robust and Unbiased Variance of GLM Coefficients for Misspecified Autocorrelation and Hemodynamic Response Models in fMRI

International Journal of Biomedical Imaging, 2009
As a consequence of misspecification of the hemodynamic response and noise variance models, tests on general linear model coefficients are not valid. Robust estimation of the variance of the general linear model (GLM) coefficients in fMRI time series is ...
Lourens Waldorp
doaj   +1 more source

Spatial Smoothing Techniques for the Assessment of Habitat Suitability [PDF]

, 2006
Precise knowledge about factors influencing the habitat suitability of a certain species forms the basis for the implementation of effective programs to conserve biological diversity.
Hothorn, Torsten, Kneib, Thomas, Müller, Jörg   +2 more
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Efficiency of local minima and GLM techniques in sinkhole extraction from a LiDAR-based terrain model

International Journal of Digital Earth, 2019
The aim of this paper was to study reliable automated delineation possibilities of karst sinkholes using a LiDAR-based digital terrain model (DTM) with pixel-based classifications.
Péter Enyedi, Melinda Pap, Zoltán Kovács, László Takács-Szilágyi, Szilárd Szabó   +4 more
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Bayesian Credibility for GLMs [PDF]

, 2018
We revisit the classical credibility results of Jewell and B\"uhlmann to obtain credibility premiums for a GLM using a modern Bayesian approach. Here the prior distributions can be chosen without restrictions to be conjugate to the response distribution.
Garrido, José, Xacur, Oscar Alberto Quijano   +1 more
core   +2 more sources

Single Trial Decoding of Belief Decision Making from EEG and fMRI Data Using ICA Features

Frontiers in Human Neuroscience, 2013
The complex task of assessing the veracity of a statement is thought to activate uniquely distributed brain regions based on whether a subject believes or disbelieves a given assertion.
Pamela eDouglas, Edward eLau, Ariana eAnderson, Wesley eKerr, Austin eHead, Margalit Aliza Wollner, Daniel eMoyer, Michael eDurnhofer, Wei eLi, Jen eBramen, Mark S Cohen   +10 more
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Functional transcranial Doppler: Selection of methods for statistical analysis and representation of changes in flow velocity

Health Science Reports, 2021
Introduction Transcranial Doppler (TCD) is a method used to study cerebral hemodynamics. In the majority of TCD studies, regression analysis and analysis of variance are the most frequently applied statistical methods.
Stephan T. Egger, Julio Bobes, Erich Seifritz, Stefan Vetter, Daniel Schuepbach   +4 more
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Improving the Sensitivity of Task-Related Functional Magnetic Resonance Imaging Data Using Generalized Canonical Correlation Analysis

Frontiers in Human Neuroscience, 2021
General Linear Modeling (GLM) is the most commonly used method for signal detection in Functional Magnetic Resonance Imaging (fMRI) experiments, despite its main limitation of not taking into consideration common spatial dependencies between voxels ...
Emmanouela Kosteletou, Panagiotis G. Simos, Panagiotis G. Simos, Eleftherios Kavroulakis, Despina Antypa, Thomas G. Maris, Athanasios P. Liavas, Paris A. Karakasis, Efrosini Papadaki, Efrosini Papadaki   +9 more
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Using the General Linear Model to Improve Performance in fNIRS Single Trial Analysis and Classification: A Perspective

Frontiers in Human Neuroscience, 2020
Within a decade, single trial analysis of functional Near Infrared Spectroscopy (fNIRS) signals has gained significant momentum, and fNIRS joined the set of modalities frequently used for active and passive Brain Computer Interfaces (BCI).
Alexander von Lühmann, Alexander von Lühmann, Antonio Ortega-Martinez, David A. Boas, Meryem Ayşe Yücel   +4 more
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Dual processing streams in chemosensory perception

Frontiers in Human Neuroscience, 2012
Higher order sensory processing follows a general subdivision into a ventral and a dorsal stream for visual, auditory, and tactile information. Object identification is processed in temporal structures (ventral stream), whereas object localization leads ...
Johannes eFrasnelli, Johannes eFrasnelli, Johan N Lundström, Johan N Lundström, Veronika eSchöpf, Simona eNegoias, Thomas eHummel, Franco eLepore   +7 more
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Voxel selection in fMRI data analysis based on sparse representation [PDF]

, 2009
Multivariate pattern analysis approaches toward detection of brain regions from fMRI data have been gaining attention recently. In this study, we introduce an iterative sparse-representation-based algorithm for detection of voxels in functional MRI (fMRI)
Feng, Jianfeng, Gu, Zhenghui, Guan, Cuntai, Li, Yuanqiang, Namburi, Praneeth, Yu, Zhuliang   +5 more
core   +1 more source